The primary goal of this project is to provide the infrastructure for the Critical Assessment of Protein Structure Prediction (CASP) prediction experiments. With the success of the sequencing projects, the structural characterization of the genome-encoded proteins becomes increasingly important. Extensive knowledge of protein structure will significantly aid the investigation of protein function, protein interactions, and biochemical pathways. It will also have a major impact on our understanding of biology and human disease, and eventually on drug design. Experimental determination of structure is inherently time-consuming and costly. Currently there is a two order-of-magnitude gap in numbers between proteins characterized by sequencing and by structure determination efforts. Computational techniques of structure modeling and prediction hold great promise for narrowing this gap. The CASP process was established to answer two main questions: First, what level of prediction quality can be expected of these techniques? And second, which methods offer the most promise for continued development? CASP is a community-wide program, with approximately 200 research groups world-wide submitting over 40,000 predictions in the last round. Our group is the primary infrastructure resource for CASP, and handles processing of predictions, develops and implements evaluation software, performs prediction assessment, develops analysis and display tools, and facilitates access to predictions and their evaluation data. We propose to support the continuing operation of CASP and to expand its infrastructure, including an increased capacity for assessing predictions, further development and refinement of the evaluation software, and improved prediction analysis methods. In addition, we will conduct a series of specialized off-CASP experiments dedicated to overcoming the most significant obstacles to progress in structure prediction. We will also provide the infrastructure for a community-wide program to build useful structural models of biologically important proteins. Finally, we will place special emphasis on interactions with lecturers and researchers throughout academia with the goal of disseminating the experience and the wealth of data gained through CASP.